@article{3166449ad63f434781bdf5eb76da064a,
title = "From single drug targets to synergistic network pharmacology in ischemic stroke",
abstract = "Drug discovery faces an efficacy crisis to which ineffective mainly single-target and symptom-based rather than mechanistic approaches have contributed. We here explore a mechanism-based disease definition for network pharmacology. Beginning with a primary causal target, we extend this to a second using guilt-by-association analysis. We then validate our prediction and explore synergy using both cellular in vitro and mouse in vivo models. As a disease model we chose ischemic stroke, one of the highest unmet medical need indications in medicine, and reactive oxygen species forming NADPH oxidase type 4 (Nox4) as a primary causal therapeutic target. For network analysis, we use classical protein-protein interactions but also metabolite-dependent interactions. Based on this protein-metabolite network, we conduct a gene ontology-based semantic similarity ranking to find suitable synergistic cotargets for network pharmacology. We identify the nitric oxide synthase (Nos1 to 3) gene family as the closest target to Nox4. Indeed, when combining a NOS and a NOX inhibitor at subthreshold concentrations, we observe pharmacological synergy as evidenced by reduced cell death, reduced infarct size, stabilized blood-brain barrier, reduced reoxygenation-induced leakage, and preserved neuromotor function, all in a supraadditive manner. Thus, protein-metabolite network analysis, for example guilt by association, can predict and pair synergistic mechanistic disease targets for systems medicine-driven network pharmacology. Such approaches may in the future reduce the risk of failure in single-target and symptom-based drug discovery and therapy.",
keywords = "network pharmacology, stroke, NOX4, network analysis, HYDROGEN-PEROXIDE, NITRIC-OXIDE, OFF-TARGET, OXYGEN, SIMILARITY, PREDICTION, EXPRESSION, BIOLOGY, BRAIN, CELLS",
author = "Casas, {Ana I.} and Hassan, {Ahmed A.} and Larsen, {Simon J.} and Vanessa Gomez-Rangel and Mahmoud Elbatreek and Kleikers, {Pamela W. M.} and Emre Guney and Javier Egea and Lopez, {Manuela G.} and Jan Baumbach and Schmidt, {Harald H. H. W.}",
note = "Funding Information: ACKNOWLEDGMENTS. This study was supported by the ERC (Advanced Investigator Grant 294683/RadMed and Proof-of-Concept Grant 737586/ SAVEBRAIN, both to H.H.H.W.S.), Spanish Ministry of Economy and Competence (SAF2015-63935R to M.G.L.), Fondo de Investigaciones Sanitarias (Instituto de Salud Carlos III/Fondo Europeo de Desarrollo Regional) (Pro-grama Miguel Servet: CP14/00008, PI16/00735), Fundaci{\'o}n Mutua Madrile{\~n}a (J.E.), short-term scientific missions by the COST Actions EU-ROS and Open-MultiMed, and Kootstra Talented Fellowship (UM) (to A.I.C.). J.B.{\textquoteright}s work was financially supported by VILLUM Young Investigator Grant 13154. J.B. and H.H.H.W.S. also received support from H2020 Project 777111-REPO-TRIAL. Funding Information: This study was supported by the ERC (Advanced Investigator Grant 294683/RadMed and Proof-of-Concept Grant 737586/ SAVEBRAIN, both to H.H.H.W.S.), Spanish Ministry of Economy and Competence (SAF2015-63935R to M.G.L.), Fondo de Investigaciones Sanitarias (Instituto de Salud Carlos III/Fondo Europeo de Desarrollo Regional) (Pro-grama Miguel Servet: CP14/00008, PI16/00735), Fundaci{\'o}n Mutua Madrile{\~n}a (J.E.), short-term scientific missions by the COST Actions EU-ROS and Open-MultiMed, and Kootstra Talented Fellowship (UM) (to A.I.C.). J.B.{\textquoteright}s work was financially supported by VILLUM Young Investigator Grant 13154. J.B. and H.H.H.W.S. also received support from H2020 Project 777111-REPO-TRIAL. Publisher Copyright: {\textcopyright} 2019 National Academy of Sciences. All Rights Reserved.",
year = "2019",
month = apr,
day = "2",
doi = "10.1073/pnas.1820799116",
language = "English",
volume = "116",
pages = "7129--7136",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "National Academy of Sciences",
number = "14",
}